TL;DR

On with Advent of Code puzzle 21 from 2022: I came up with a simple equation but…

After day 19, that took me so long, this day’s puzzle was pretty straightforward. I guess it’s a matter of knowing how to do things beforehand.

Both parts largely require us to evaluate/manipulate arithmetic expressions comprised of sums/subtractions/multiplications/divisions (integer ones, as it happened in my case at least); the second part twist is that one of the operations has to be considered an equal sign, one of the inputs is an unknown variable and the whole thing is an equation that we have to solve for the unknown.

I guess it might sound difficult, but if we think about it, we lucky folks are teached how to do these operations (and their inverse) in the first years of our education, so it’s no big deal to translate these rules.

First we have to read the inputs, though. Each line is an expression, which consists either in a value or an operation; it makes sense to parse the lines as such so here we go:

for $filename.IO.lines ->$expression {
my $match =$expression ~~ m{^
$<target>=(\w+) \:\s+$<op1>=(\w+)
[ \s+ $<op>=(\S) \s+$<op2>=(\w+) ]?
$}; my$nv = nv($match<target>); if$match<op> {
$nv.init(nv($match<op1>), $match<op>, nv($match<op2>));
}
else {
$nv.init($match<op1>.Int);
}
}


As we will deal with expressions, it makes sense (to me) to represent each operation in an expression, or a single value, as a Node, and keep track of all nodes (this is the nv() function used above):


class Node {
has $.name; has$.value = Nil;
has $.left = Nil; has$.right = Nil;
has $.op = Nil; multi method init ($value) { $!value =$value }
multi method init ($left, Str()$op, $right) {$!left  = $left;$!right = $right;$!op    = $op; } ... } ... sub nv (Str()$name) { # keep track of all nodes
state %node-for;
return %node-for{$name} //= Node.new(name =>$name);
}


As it happens, the inputs are simple, in the sense that what we have out of the inputs is a tree instead of a more generic graph. In other terms, each four-letters placeholder only appears once on the left and at most once on the right across all expressions; this simplifies things a lot for part 2.

Anyway, part 1 is about evaluating the whole thing, with root at the… root or our evaluation tree. Many people went the eval route, which is fair in these challenges; I opted for a more canonical and boring solution, involving doing the maths step by step. I guess there was a quick shortcut do express this in Raku but… I don’t know it.

class Node {
...

method simplified {
return $!value if defined$!value;
my $left =$!left.simplified;
my $right =$!right.simplified;
return "($left$.op $right)" unless$left ~~ Int && $right ~~ Int; return$!op eq '+' ?? $left +$right
!! $!op eq '-' ??$left  -  $right !!$!op eq '*' ?? $left *$right
!! $!op eq '/' ??$left div $right !! die("unknown op$.op");
}

...
}


If the node is a simple value, just return it. Otherwise, do the simplification of the expression on both sides, and apply the operation. As anticipated, I went for integer arithmetics and it was fine for my inputs.

The twist in part 2 is that the meaning of two items change:

• the operation in the root node is an equal sign actually, turning the whole thing into an equation instead of a simple expression;
• the value in the humn node should be disregarded and we have to find out the right one to make the whole equation hold.

I initially thought of printing the equation and throwing it to Wolfram Alpha. But… I hit (like many others) the wall of the maximum input lenght, so I was back to square zero. Ouch!

The fact that the equation is represented by a tree comes to the rescue here. My approach is to simplify the equation until I have the unknown alone on one side, and a value on the other; with a tree, I have that the unknown is only on one side at each step (even though “not alone”), while the other side is always a simple number. Something like this:

$f_i(x) = K$

Now, f_i(x) is by itself an arithmetic expression that involves basic operations upon our unknown humn/$x$ variable, so we can invert it and obtain a new equation that has the same shape. As an example, let’s consider we have this at step $i$ of our simplification:

$f_i(x) = A + f_{i+1}(x)$

This means:

$A + f_{i+1} = k \Rightarrow f_{i+1} = K - A$

A couple examples more, also keeping in mind that subtraction and division are not commutative:

$A * f_{i+1}(x) = K \Rightarrow f_{i+1}(x) = K / A \\ f_{i+1}(x) / A = K \Rightarrow f_{i+1}(x) = K * A \\ A / f_{i+1}(x) = K \Rightarrow f_{i+1}(x) = A / K$

In our tree, then, we will have almost always three terms that we are interested into:

• the side with a simple value, i.e. $K$
• the side with an operation, which has two operands $A$ and $f_{i+1}(x)$

We have to take care of the order of the operands in the operation, but it’s really no big deal as we have to take into account only a few possibilities. Here’s the final product:

class Node {
...

method set-as-unknown { $!value = 'x' } method !expr-value { my$rv = $!right.simplified; return ($!left, $rv) if$rv ~~ Int;
return ($!right,$!left.simplified);
}

method solve-as-equal {
my ($expr,$value) = self!expr-value;

while $expr.simplified ne 'x' { my$op = $expr.op; if$op ~~ m{ <[ + * ]> } { # commutative
my ($se,$sv) = $expr!expr-value;$expr = $se;$value = $op eq '+' ??$value - $sv !!$value div $sv; } elsif$op ~~ m{ <[ / - ]> } {  # non-commutative
my ($l,$r) = $expr.left,$expr.right;
if $l.simplified ~~ Int { # K <op> f(x) = V --> f(x) = K <op> V$expr = $r;$value = $op eq '-' ??$l.simplified - $value !!$l.simplified div $value; } else { # f(x) <op> K = V --> f(x) = V <inv-op> K$expr = $l;$value = $op eq '-' ??$value + $r.simplified !!$value * $r.simplified; } } else { die "unknown op$op" }
}

return $value; } ... }  The set-as-unknown() method allows us to set node humn a our unknown variable; then solve-as-equal() does the whole job of taking different alternatives into consideration and applying the transformation that eventually lead us to x = K_n, that is our solution. To account for the modification in the root node, this method is called onto that specific node; additionally, at each step we make sure that $expr contains the expression with the unknown, and $value is our$K\$ from the discussion above.

With this said… have fun and stay safe!